Reading Reports in Google Analytics: Recency


Do you know how to read the recency report in Google Analytics? I sure didn’t.So I reverse engineered it — and here, come learn with me what it’s all about when they say, “Most people visited your site 0 days ago…”

Methodology. All great scientific experiments start with a boring chapter on methodology. (Right?) So here is mine: In order to test, I created a number of profiles where my home computer was the only “person” in the profile. Then, I was able to learn how GA computed recency when there was only one unique visitor, and where I knew exactly when she (that’s me!) had visited, and if she had wiped her cookies.

Here is what I learned:

Recency is about visits, not visitors.

When the report says, “Most people visited 1 day ago” — that’s just a typo. The report isn’t about people, or unique visitors. It is about visits. If you have any doubt, look at the column with the numbers in it. It says, “visits.” Then, whip out your calculator, add them up, and without changing the calendar, head on over to the Visitor > Visit Trending > Visits report. If they aren’t the same number, then comment here. Send me email. Call me on my cell phone.

I want to say this a different way. If you have 100 visits in the time period, there will be exactly 100 visits in the recency chart. Even if they all come from the same person’s computer.

Recency computes time (in seconds) between each visit from the same visitor. If the time between visits is less than 24 hours, it will show up as a Zero Days Ago visit.

Before I explain this one, let me show you the results of one of my tests. It will make it easier to explain.

recency-excel-luna.jpgWithout wiping my cookies, I set up a new profile for the LunaMetrics website, and created a user defined variable that had only myself in it. Then I visited. Here is when I visited — you can see the 24 hour clock down the left margin.

Now, I will take you on a tour of all these visits. At some level, this is incredibly boring, like all good scientific experiments. (I’m sorry. The truth is that I don’t have the definitive word on recency, so the best I can do is show you the evidence. Sort of like CSI.)

OK, for those of you who are still with me: All the visits that aren’t in a colored block had a visit right before it that was less than 24 hours earlier. So, for example, on November 16, I only visited once, at 7 am, but the visit before it was on the 15th at 19:00 — only about 10 hours earlier. Every single one of these non-colored visits will get a notch in the zero days ago category. (Right? If recency is time between visits, and there are only 10 hours between two visits, they are less than a day apart, so the earlier visit gets classified as zero days before the later visit.)

But what about those visits in the colored blocks? Let’s start with the two visits at 9 am on the 22nd (orange). I visited twice in one hour. One visit was probably 45 minutes or so before the other — clearly less than 24 hours before it, and it shows up as zero days. The other orange visit was preceded by the green visit. Notice that there are more than 24 hours between the one in green and the one in orange. So now we have a visit in the 1 Day Ago category.

Now look at Yellow, on the 17th. This is just like Orange: two visits in one hour, one of them clearly less than 24 hours before the other, and the other, more than 24 hours ago. Another 1 Day Ago visit.

OK, we will turn our eyes (if we haven’t gone to sleep yet) to Green on the 20th at 18:00 (6 pm).I didn’t even visit the day before. The prior visit was MORE THAN 48 HOURS before it. So that one will show up as Two Days Ago. (Go team!)

And finally, the first box, in blue. I don’t have records for when I visited before this date — I just started this profile on the day that I started the test, but I didn’t clear my cookies. This part is very important: The recency chart cares about visits outside the time you picked, as long as they are affiliated with a visit that is inside the time period. For example: If my most recent visit before the very first one, i.e. the blue one, had been 7 days ago, it would show up in the 7 day bar, even though that is outside the time period.

OK, let’s summarize. Of the 16 times in this period I visited, 12 of them had a prior visit that was less than 24 hours before it (0 days ago), two (an orange and a yellow) had a prior visit that was just over 24 hours before (1 day ago ), one had a prior visit that was two days ago (the green one) and one of them (the blue one) is in the “I’m not sure” category.

So if I pull the recency chart for the period of November 13-22, here is what it looks like:


So in this ten day period, we had one person (me) visit 16 times, and most of those visits were preceded by a more recent visit that took place less than one day before it. That’s what they mean when they say, “Most people last visited: 0 days ago.”

And moving right along: Very frequent visits are in the same zero days bucket with new visits. This is bad.

I set up about five different tests. Here is a different one that I set up on November 14. This time, I cleared all the necessary cookies, so that GA would think I had never been there before, but would still know to measure only me — and I visited on November 14, but not on the 15th or 16th:


The reason this is bad is that GA throws together visitors who visit the site often with visitors who are new. A content site might find that repeat customers are more likely to continue repeating (so they are the best visitors) and that new visitors may come back or bail (so they are question marks.) Those aren’t two categories we really want to combine.

So here are the takeaways and “to do’s” :

  • If you care about recency, create a returning visitors profile by using a filter to exclude new visitors (Need to learn how to create a custom filter?). If you see lots of visits in 0 days ago in this Returning Visitors profile, you are seeing visits from visitors who come back quickly. In fact, this chart is pretty hard to read, so the more you segment, the more you will learn.
  • Forget the line that says, “Most people last visited.” Just read the report and come to your own conclusions.

Let me close with two thoughts:

  1. I can’t stress enough how every visit during the period gets a matching visit that is the one that came just before it.
  2. I can’t stress enough how this is just my experiment. Go ahead, create your own. Prove me wrong. I would love to see it.

Whew. This took a long, long time to do. Many thanks to everyone who tried to help.

Our founder, Robbin Steif, started LunaMetrics in 2004. She is a graduate of Harvard College and the Harvard Business School, and has served on the Board of Directors for the Digital Analytics Association. Robbin is a winner of a BusinessWomen First award, as well as a Diamond Award for business leadership. In 2017, Robbin sold her company to HS2 Solutions and has since retired from LunaMetrics.

  • Loren Hadley

    Thanks for the post – it explains a lot. I also appreciated the takeaway of how to segment new versus returning.

  • steve

    “in my usual maverick fashion…”
    *snort*. No idea what you mean. Uh Uh. None. What. So. Ever! 😀

    I think my brain hurts from reading that and trying to “get it”.
    But I for one, and eventually my boss, clients et al, will appreciate your efforts to generate this Robbin!

    Much Thanks!
    – Steve

  • reflekt

    Thanks a lot, I was trying to get some useful information from this report and had the same hypotheses but could not validate them. GA can be misleading sometimes…

  • That makes a lot of sense. Thanks for explaining those results. I agree with Loren and really appreciate the segmentation idea to separate the new (less productive) traffic and the repeats. As for the length of the post, at least people cant say you aren’t thorough!

  • Thank you so much — you have a lot of good information there, and I appreciate you taking the time to do the investigate work that few of us have patience for!

  • Meaghan

    Thank you for this wonderful breakdown, it’s incredibly helpful!

  • Meaghan

    It’s still wonderful! However I now have more questions since I’ve had a night to think about this.

    So, if someone visited my site 10 months ago, 22 hours ago and today, there would be marks in the 121-364 days ago column and two in the zero days ago column because there was a space of ten months between visits then a space of less than a day; giving three marks. I think I followed all of that correctly.

    However, is it possible to see how long it has been since a returning visitor has been to the site? i.e. if someone visited just once, ten months ago, would it ever be possible to see that they haven’t come back and how long ago they visited?

  • Meaghan — yes, your analysis is correct for that person who visits three times. As far as your question about a specific visitor, you aren’t technically allowed to track at the individual level. But, you might frame the question differently, like this: people who came on my campaign for Spring 2007 flowers, how many of them came back and when? So it is the same question you posed, but I grouped them into a category of people who came on a specific campaign.

    Then, you can set up a special profile (hopefully, as soon as the campaign happens) to track just those individuals who had that cookie (e.g. &utm_campaign=SpringFlowers2008, etc.) Then your charts will be about them only.

    One of your problems will be that the loyalty charts (Loyalty, Recency, Depth and Length) are about visits, not visitors. Despite the fact that they say “people” in them. So you might have one person out of the millions who first came on that campaign, visiting and revisiting and revisiting. I can think of some javascript ways to get around that one, mostly involving John Henson’s blog post here on getting more than one value in your setvar. Here is that article link:

  • Hi, I just signed onto this sit. I have had a website for approx. 4 years now. People visit the site all the time. When I looked at the report of my website it had all zeros for everything. Do I need to do something to get the information up and running:
    Any help would be appreciated.

  • Hi Louise. Yes, you have to put the Google Analytics code on your page. You need to have access to your website to do that, otherwise, you will always see zeros. Here is an article for you:

  • Silvano

    Thanks for the explanation. It explains the numbers I see…. still seeing something like “I received 60 visits 0 days ago” when I only had, say, only 4 visitors in the last 2 days, makes no sense whatsoever. What it should really say is “60 visits occurred less than 24 hours after the first visit…” Is this the correct understanding?

  • Almost!

    It should have said, “60 visits occurred from visitors who last visited less than 24 hours ago.” This probably seems like a very fine distinction, but you could have one visitor (like me, in the test) that was in the 0 days bucket, slipped into the 1 day bucket (let 24 hours go by) and then had a bunch of visits in the 0 days bucket. So the immediately prior visit didn’t have to be their *first* visit.

  • Dan

    It’s all a little confusing to me, but I’m starting to get it. Here’s my problem with GA. I have a local brick and mortar business. The goal of my website is to drive people into my B&M business. While it’s nice to see the traffic from around the world; I’m really only concerned with local traffic. Is there a way to make a filter that will show me only local traffic (IE: traffic from Hamilton County, TN). Any help will be greatly appreciated. PS: You can send me an email explaining how to set up a local filter. djbrownell[at]comcast[dot]net

  • Dan – you can either create a filter by city or by state. City is probably a little too small (because they might live just outside Hamilton County. And their computer might live a few cities over, which is what really matters.) State might be a little too big, but I would go for state if I were you and then look through all the cities within the state.

    Here is how you do it: First, create a new profile so that you will only be filtering data in your new profile and not in the data that you already have. (I know, you want to do that, filter the old data, but you can’t — Google won’t let you go back in time like that – so you might as well have a new profile so that you can make mistakes safely.) Next, choose filter manager from the main three options on the bottom of page you get right after you created the new profile. Next, choose “Add Filter” which is hard to find, because it is in white type on a dark background. Give it a friendly name, like, Tennessee Only. For Filter type, choose custom filter. Suddenly, you will get lots of choices. Choose the “include” option. Choose “visitor region” from the filter field drop down box. In the final box, filter pattern, you have to type Tennessee. I am pretty sure GA uses the whole name and not abbreviations (not that I have ever seen), so you should be safe with that. Finally, on the left hand side of the screen, you can choose which profile you want to add this new filter to — choose your new profile ONLY. Save your work and if it isn’t working in a few days, post another comment. Robbin

  • Dan

    Thank you Robbin. I have set up the new profile. I appreciate your your help, as a thank you, I will add your link to my website.

  • Dan

    The new filter is working perfectly. I can now track my local traffic. Thanks again!

  • Thank you Dan for a great explanation of the Google Analytics recency calculation. The typo can sometimes be misleading. Have you digged in to the calculations of conversion rate in Google Analytics? Im still trying to define the problems but I seem to get very different results compared with more or less similar conversion thunnels.

  • Congratulations!
    Very good article and perfect clear explanation 🙂
    Well done 🙂
    Thank you so much,
    Marco 😉

  • Hi Robbin,
    Thank you for this post. Is it safe to say that subtracting the overall number of new visits from the 0-days-ago figure in the recency report would provide a more accurate view of the recency report? In this report, new visits should only appear in the 0-days-ago category. So if you subtract new visits from that category, the rest of the figures should appear pretty close to a recency report for that same time period in a return visitor profile. Is that an accurate assumption? Or would the percent error in this approach be greater than the inherent percent error GA accounts for across different profiles?


  • Correct, If you care about recency, create a returning visitors profile by using a filter to exclude new visitors .

    But there is no error (outside of the fact that WA aren’t 100% perfect.) Error is about predicting the future based on the past (like GWO). On the other hand, the GA says, “This is what was, pretty much. Now you go interpret it any way you want. “

  • Leo

    Thanks a lot for your post.
    The post is very clear and excellent.

  • Thanks for the great article. Still something is not clear to me. What is the aim here? In other words, what is a good looking Recency report? And how should I hope to see it change in time?
    I have 90% in “0 days ago”, does it mean that 90% of my visitors check the website more than once a day? So it’s a good thing?

    I hope my question is clear 🙂
    Can you please email me if you reply to this? Thanks you very much!

  • Thanks for a great article. Does Google’s new beta demographics remove the need to create a filter to remove new visitors? I’m interested in returning visitor behaviour. Would seeing up the filter give me an accurate count on returning visitors?

  • Gods, they’ve bungled the UI on this one.

    BTW A way to phrase it that might not make Salvatore there and others still confused afterwards is this:
    “This graphic measures the frequency of the gap between visits from the same (percieved) user, in days.”

    And then, while it’s not terribly *useful* to contain the new users as having a gap of 0, it’s technically *true* strictly speaking (well, that or infinite, depending on how you look at it).

  • blaine

    Thanks for posting this! great stuff. Good work, i read it all and it was very clear

  • A very clear explanation of a tricky situation to describe. Presumably using the returning visitor segment is just as effective as setting up a returning visitor profile? My issue is that I need to provide some analysis on some historical data and so the segment option is the only one available to me.

  • Hi Sally. In general, you can’t presume when it comes to Advanced Segments vs. profiles, but on this one, you are correct. You can use the Advanced Segment set for returning visits only.

  • I’m using GA for year-and-half now, but seems learning new things everyday (This is how I tell “things are very complicated… ;)” ). Anyway, nice article though.

  • Amit

    Hi… I know it is quite an old post but could not find a recent one and hope you would reply…U seem to have put in quite some efforts but my reports are different.

    The sum of visits in recent chart are much more than the actual visits for the same period..Please give me ur email id so that i can send you the snapshots for the same.

    I would appreciate an early reply and would be g8 to discuss some other anomalies in google analytics.

    Amit Mittal

  • Robbin

    Amit, the recency reports have changed a lot since I wrote this, specifically wrt the issue of new and returning visits.

  • Eva

    Hi Robbin, just found your article while I am trying to figure out the difference between <0 days ago and same day on Recency report. Yes it has really changed a lot since you wrote this post and I look forward to your new post on same topic! And hope you can bring light to the confusing same day vs <0 days ago visits. Thanks!

  • cherub

    great article! I’ve been going nuts how to understand this ‘days since last visit’ report! thanks! I am not able to understand what it means. explanation very clear and easy to understand!

  • cherub

    great article! I’ve been going nuts how to understand this ‘days since last visit’ report! thanks! I am now able to understand what it means. explanation very clear and easy to understand!

  • Sid

    I was looking for some information on the methodology on Recency reporting in GA and found your awesome post. I have one question I hope you can help me with. Suppose my aim is to segment my Organic and Paid traffic and figure out which one is sending users which are coming back more often (Increased Recency of vists). GA currently shows me this view when I compare both segments. My question however is, how does it bucket the paid vs organic? If a user clicked my paid ad and came to the site, and then returned via a direct visit, would he show up only in the paid category (because his first touch/click was paid?) and what happens if someone comes to the site directly at first, but then returns via a paid click. Does he get classified as a return visitor in the organic category?

    Hope that makes sense. Great if you could throw some light.


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  • Gagandeep Gupta

    Thanks Robbin for Sharing this research.. It is very very helpful.. I was totally confused between visits and visitors in Recency report and it cleared all my doubts..

    Just One Doubt: In your test,the blue tab entry should has come in 0 days since last visit (since it was your first entry.. u were new to the site) but rather came in the 1 days.. Please clear me on this..

  • Robbin

    Hi Gagandeep — note what I wrote about the blue: “And finally, the first box, in blue. I don’t have records for when I visited before this date — I just started this profile on the day that I started the test, but I didn’t clear my cookies. This part is very important: The recency chart cares about visits outside the time you picked, as long as they are affiliated with a visit that is inside the time period.” This is the hardest concept to grasp about recency, i.e. it knows that you visited before, even if your prior visit is outside the time period you have chose.

  • Ash

    Robbin, I’ve recently come across this article, which has almost made this clear to me. However, on the page, the recency charts are not showing and I would love to see what they look like to help my understanding. Is there anyway you can make these available to me? Kind regards,

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